According to the principle of fuzzy control, a predetermined set of rules are activated when an input signal is supplied to a fuzzy deduction unit, and the control action for the control object is determined by deduction according to the activated set of rules. The set of rules include a large number of fuzzy rules which are allocated for different control situations, and such fuzzy rules are typically expressed in the form of if-then statements.
Conventionally, generation of such fuzzy rules were conducted for each specific application, and it was necessary to create and modify new fuzzy rules for each new application. However, the need to create and modify fuzzy rules for each new application is highly cumbersome to the system operator, and a considerable amount of work is imposed upon the operator. Further, existing sets of rules were activated only for certain specific applications, and were not effectively utilized for creation of new sets of rules.
It is therefore preferred to be able to create a new set of rules for each new application according to existing sets of rules. However, such a process of creation would be highly cumbersome for the system operator who sets each new created fuzzy rule on a deduction unit one by one by means of a man-machine interface.
Also, since there is no standardized algorithm for defining a set of fuzzy rules which allows a fair estimation of the stability of the control process and the control performance as opposed to the case of conventional linear control systems, system designers had to depend much on trial and error processes. Therefore, not only much experience would be required to set up fuzzy rules but also a considerable time would be necessary for their set up and adjustment.